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st: Generalized partially linear models


From   "Kingombe, Christian" <christian.kingombe04@imperial.ac.uk>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   st: Generalized partially linear models
Date   Fri, 30 Oct 2009 16:29:58 +0000

Dear STATA Corp,

Partially linear models are linear regression models where one component is allowed to vary nonparametrically. Generalized partially linear models generalize this case from linear regression to the quasi-likelihood setting of standard GLIMs, thus encompassing a larger class models including logistic, Poisson, and Gamma regression. Although estimation for these models is possible in official Stata via fractional polynomials, this approach is entirely nonparametric and uses a local-linear smooth to estimate the "nonlinear" component.
The Stata command gplm for fitting generalized partially linear models is discussed and demonstrated by Roberto Gutierrez, StataCorp, on copy.
Sources: http://www.stata.com/meeting/1australia/abstracts.html 
http://www.stata.com/meeting/2german/Gutierrez.pdf 

Unfortunately, I have been unable to find this command in the STATA ssc archive. I have access to both  STATA 9.2 and STATA 10.1 but in both packages I'm informed by the help (findit) that the command doesn't exist?

Would you by any chance have any experience with this Command and if so help me get over this hurdle.

In advance thank you very much for your support

Best regards,

Christian Kingombe

PS
I know that you can carry out semi-parametric regressions in R and alternatively use the gplmest quantlet in XploRe statistical software. But, I would like to carry out my entire analysis in STATA, which is the software programme that I am most familiar with.

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